Mathematical modeling and validation of growth of Salmonella Enteritidis and background microorganisms in potato salad – One-step kinetic analysis and model development

• The Growth of Salmonella Enteritidis (SE) in potato salad was investigated.
• A one-step method was used to directly construct growth models for SE.
• The growth kinetics of background microorganisms (BK) was also investigated.
• The models were validated and can be used to predict the growth of SE and BK.

This study was conducted to examine the growth of Salmonella Enteritidis (SE) in potato salad caused by cross-contamination and temperature abuse, and develop mathematical models to predict its growth. The growth of SE was investigated under constant temperature conditions (8, 10, 15, 20, 25, 30, and 37 °C) to evaluate the effect of temperature on growth rates and lag times. Duplicated experiments were conducted. The data set from one replicate was used to develop kinetic models and determine kinetic parameters. The data from the other replicate served as an independent data set for model validation. The growth of background microorganism (BK) was also examined. One-step kinetic analysis method was used to directly construct both primary (Huang) and secondary (Ratkowsky square-root) models. Nonlinear regression was used to minimize the global residual sum of squares (RSS) for SE and BK. The results showed that both primary and secondary models can be used to analyze the growth curves, with the kinetic parameters closely matching the characteristics of SE and BK. The validation results showed that the root-mean-square error (RMSE) was only 0.40 Log CFU/g for SE and 0.66 Log CFU/g for BK, with the residual errors of predictions following Laplace and logistic distributions, respectively. This study showed that one-step kinetic analysis is a useful and efficient method for analyzing the entire data set to directly construct primary and secondary growth models and determine kinetic parameters. Since the models are validated, they can be used to predict the growth of SE and conduct risk assessment, and to predict the microbiological shelf-life of potato salad.